Overview

Dataset statistics

Number of variables15
Number of observations1452
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory181.5 KiB
Average record size in memory128.0 B

Variable types

Numeric14
Categorical1

Alerts

exp_call_price is highly overall correlated with exp_price and 10 other fieldsHigh correlation
exp_price is highly overall correlated with exp_call_price and 8 other fieldsHigh correlation
exp_price_kurtosis is highly overall correlated with exp_call_price and 2 other fieldsHigh correlation
exp_price_max is highly overall correlated with exp_call_price and 8 other fieldsHigh correlation
exp_price_median is highly overall correlated with exp_call_price and 8 other fieldsHigh correlation
exp_price_min is highly overall correlated with exp_call_price and 8 other fieldsHigh correlation
exp_price_q1 is highly overall correlated with exp_call_price and 8 other fieldsHigh correlation
exp_price_q3 is highly overall correlated with exp_call_price and 8 other fieldsHigh correlation
exp_price_skew is highly overall correlated with exp_call_price and 2 other fieldsHigh correlation
exp_price_std is highly overall correlated with exp_call_price and 10 other fieldsHigh correlation
last_quote is highly overall correlated with exp_call_price and 8 other fieldsHigh correlation
strike is highly overall correlated with exp_call_price and 8 other fieldsHigh correlation
exp_price has unique valuesUnique
exp_call_price has unique valuesUnique
exp_price_min has unique valuesUnique
exp_price_max has unique valuesUnique
exp_price_std has unique valuesUnique
exp_price_median has unique valuesUnique
exp_price_q1 has unique valuesUnique
exp_price_q3 has unique valuesUnique
exp_price_kurtosis has unique valuesUnique
exp_price_skew has unique valuesUnique

Reproduction

Analysis started2024-02-12 15:08:51.791243
Analysis finished2024-02-12 15:09:18.752024
Duration26.96 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

last_quote
Real number (ℝ)

HIGH CORRELATION 

Distinct1388
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean355.96338
Minimum222.21
Maximum477.77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.7 KiB
2024-02-12T16:09:18.868029image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum222.21
5-th percentile265.072
Q1288.1075
median357.78
Q3418.6425
95-th percentile456.678
Maximum477.77
Range255.56
Interquartile range (IQR)130.535

Descriptive statistics

Standard deviation68.853394
Coefficient of variation (CV)0.19342831
Kurtosis-1.4822943
Mean355.96338
Median Absolute Deviation (MAD)67.225
Skewness0.07395125
Sum516858.83
Variance4740.7899
MonotonicityNot monotonic
2024-02-12T16:09:19.029698image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
280.99 3
 
0.2%
298.09 3
 
0.2%
396.46 3
 
0.2%
274.51 3
 
0.2%
415.24 2
 
0.1%
269.11 2
 
0.1%
311.66 2
 
0.1%
273.35 2
 
0.1%
289.48 2
 
0.1%
272.06 2
 
0.1%
Other values (1378) 1428
98.3%
ValueCountFrequency (%)
222.21 1
0.1%
228.95 1
0.1%
234.34 1
0.1%
239.75 1
0.1%
240.72 1
0.1%
240.94 1
0.1%
241.23 1
0.1%
242 1
0.1%
244.09 1
0.1%
246.02 1
0.1%
ValueCountFrequency (%)
477.77 1
0.1%
477.56 1
0.1%
477.48 1
0.1%
477.26 1
0.1%
476.92 1
0.1%
476.73 1
0.1%
476.47 1
0.1%
476.14 1
0.1%
475.31 1
0.1%
475.08 1
0.1%

strike
Real number (ℝ)

HIGH CORRELATION 

Distinct279
Distinct (%)19.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean355.95248
Minimum222
Maximum478
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.7 KiB
2024-02-12T16:09:19.196520image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum222
5-th percentile265
Q1288
median358
Q3419
95-th percentile457
Maximum478
Range256
Interquartile range (IQR)131

Descriptive statistics

Standard deviation68.859968
Coefficient of variation (CV)0.1934527
Kurtosis-1.4815996
Mean355.95248
Median Absolute Deviation (MAD)67
Skewness0.073974302
Sum516843
Variance4741.6952
MonotonicityNot monotonic
2024-02-12T16:09:19.352583image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
279 24
 
1.7%
265 19
 
1.3%
288 18
 
1.2%
275 17
 
1.2%
270 17
 
1.2%
290 15
 
1.0%
412 14
 
1.0%
285 14
 
1.0%
438 14
 
1.0%
434 14
 
1.0%
Other values (269) 1286
88.6%
ValueCountFrequency (%)
222 1
 
0.1%
229 1
 
0.1%
234 1
 
0.1%
240 1
 
0.1%
241 3
0.2%
242 1
 
0.1%
244 1
 
0.1%
246 2
0.1%
247 2
0.1%
248 4
0.3%
ValueCountFrequency (%)
478 3
0.2%
477 3
0.2%
476 2
 
0.1%
475 2
 
0.1%
474 1
 
0.1%
473 1
 
0.1%
472 2
 
0.1%
471 3
0.2%
470 5
0.3%
469 6
0.4%

exp_price
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1452
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean356.41852
Minimum223.11144
Maximum478.4213
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.7 KiB
2024-02-12T16:09:19.649440image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum223.11144
5-th percentile265.44888
Q1288.30372
median358.28119
Q3419.20273
95-th percentile457.28118
Maximum478.4213
Range255.30986
Interquartile range (IQR)130.89901

Descriptive statistics

Standard deviation68.970285
Coefficient of variation (CV)0.19350927
Kurtosis-1.4845172
Mean356.41852
Median Absolute Deviation (MAD)67.43622
Skewness0.074650849
Sum517519.69
Variance4756.9003
MonotonicityNot monotonic
2024-02-12T16:09:19.854563image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
269.0778639 1
 
0.1%
468.7045789 1
 
0.1%
469.3887794 1
 
0.1%
470.1236127 1
 
0.1%
468.5389232 1
 
0.1%
469.5602465 1
 
0.1%
467.8786601 1
 
0.1%
467.6683735 1
 
0.1%
464.1990265 1
 
0.1%
464.071113 1
 
0.1%
Other values (1442) 1442
99.3%
ValueCountFrequency (%)
223.1114437 1
0.1%
229.8626144 1
0.1%
234.7220296 1
0.1%
240.5365507 1
0.1%
241.0879632 1
0.1%
241.8562739 1
0.1%
242.0966019 1
0.1%
242.9177255 1
0.1%
244.5624423 1
0.1%
246.4588983 1
0.1%
ValueCountFrequency (%)
478.4213023 1
0.1%
478.2455147 1
0.1%
478.1551292 1
0.1%
478.0082159 1
0.1%
477.6053332 1
0.1%
477.4394785 1
0.1%
477.2185417 1
0.1%
476.8173134 1
0.1%
475.9704084 1
0.1%
475.7089922 1
0.1%

exp_call_price
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1452
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.3139035
Minimum3.8886722
Maximum12.843307
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.7 KiB
2024-02-12T16:09:20.055259image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum3.8886722
5-th percentile4.3799085
Q15.2105621
median7.3870524
Q38.9995545
95-th percentile10.605908
Maximum12.843307
Range8.9546345
Interquartile range (IQR)3.7889924

Descriptive statistics

Standard deviation2.1099548
Coefficient of variation (CV)0.28848546
Kurtosis-1.0722277
Mean7.3139035
Median Absolute Deviation (MAD)1.9038192
Skewness0.15614594
Sum10619.788
Variance4.4519092
MonotonicityNot monotonic
2024-02-12T16:09:20.285899image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.798478111 1
 
0.1%
8.220066103 1
 
0.1%
8.09644625 1
 
0.1%
7.788127405 1
 
0.1%
8.11806613 1
 
0.1%
7.96786072 1
 
0.1%
8.304719144 1
 
0.1%
8.274465142 1
 
0.1%
7.809494119 1
 
0.1%
8.08622683 1
 
0.1%
Other values (1442) 1442
99.3%
ValueCountFrequency (%)
3.888672245 1
0.1%
3.935747798 1
0.1%
3.979069894 1
0.1%
4.010295821 1
0.1%
4.020190645 1
0.1%
4.063195007 1
0.1%
4.071811848 1
0.1%
4.073157903 1
0.1%
4.077003118 1
0.1%
4.090780106 1
0.1%
ValueCountFrequency (%)
12.8433067 1
0.1%
12.77666057 1
0.1%
12.54416727 1
0.1%
12.53490069 1
0.1%
12.51332678 1
0.1%
12.31507692 1
0.1%
12.25254336 1
0.1%
12.24936321 1
0.1%
12.20926828 1
0.1%
12.20683473 1
0.1%

exp_price_min
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1452
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean281.6167
Minimum139.7242
Maximum387.84669
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.7 KiB
2024-02-12T16:09:20.442652image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum139.7242
5-th percentile205.40597
Q1236.25548
median280.71039
Q3326.05074
95-th percentile362.71372
Maximum387.84669
Range248.12249
Interquartile range (IQR)89.79526

Descriptive statistics

Standard deviation52.598425
Coefficient of variation (CV)0.1867731
Kurtosis-1.0663781
Mean281.6167
Median Absolute Deviation (MAD)44.882307
Skewness-0.005753378
Sum408907.45
Variance2766.5943
MonotonicityNot monotonic
2024-02-12T16:09:20.637927image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
214.1313836 1
 
0.1%
386.9805482 1
 
0.1%
385.0966538 1
 
0.1%
387.5691339 1
 
0.1%
379.5108775 1
 
0.1%
387.8458186 1
 
0.1%
378.2786375 1
 
0.1%
379.4523784 1
 
0.1%
381.3933389 1
 
0.1%
376.3941101 1
 
0.1%
Other values (1442) 1442
99.3%
ValueCountFrequency (%)
139.7241985 1
0.1%
152.8273534 1
0.1%
156.7008612 1
0.1%
160.3637264 1
0.1%
160.7717765 1
0.1%
161.7513442 1
0.1%
163.4167352 1
0.1%
163.5025405 1
0.1%
164.0366143 1
0.1%
164.6383969 1
0.1%
ValueCountFrequency (%)
387.846685 1
0.1%
387.8458186 1
0.1%
387.5691339 1
0.1%
387.354801 1
0.1%
386.9805482 1
0.1%
385.9601061 1
0.1%
385.0966538 1
0.1%
383.4142857 1
0.1%
382.9438382 1
0.1%
382.9240989 1
0.1%

exp_price_max
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1452
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean450.6273
Minimum307.46582
Maximum627.75804
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.7 KiB
2024-02-12T16:09:20.821610image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum307.46582
5-th percentile332.57858
Q1353.56144
median452.31935
Q3534.88332
95-th percentile589.00038
Maximum627.75804
Range320.29222
Interquartile range (IQR)181.32187

Descriptive statistics

Standard deviation93.023436
Coefficient of variation (CV)0.20643098
Kurtosis-1.521059
Mean450.6273
Median Absolute Deviation (MAD)92.616499
Skewness0.10874658
Sum654310.85
Variance8653.3596
MonotonicityNot monotonic
2024-02-12T16:09:21.060927image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
327.5079646 1
 
0.1%
567.1340376 1
 
0.1%
567.2630514 1
 
0.1%
568.8660174 1
 
0.1%
561.367893 1
 
0.1%
565.5923145 1
 
0.1%
564.9838079 1
 
0.1%
573.355339 1
 
0.1%
572.0785293 1
 
0.1%
563.914212 1
 
0.1%
Other values (1442) 1442
99.3%
ValueCountFrequency (%)
307.4658183 1
0.1%
314.2481051 1
0.1%
319.6220708 1
0.1%
320.0047015 1
0.1%
320.8542826 1
0.1%
320.881408 1
0.1%
321.1726132 1
0.1%
321.9185636 1
0.1%
322.3905809 1
0.1%
322.5112284 1
0.1%
ValueCountFrequency (%)
627.7580387 1
0.1%
626.8902763 1
0.1%
626.5218105 1
0.1%
623.1727269 1
0.1%
621.402897 1
0.1%
618.7804862 1
0.1%
617.8437287 1
0.1%
617.4170714 1
0.1%
616.6111765 1
0.1%
616.3685879 1
0.1%

exp_price_std
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1452
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.781087
Minimum9.8381527
Maximum29.94628
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.7 KiB
2024-02-12T16:09:21.237316image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum9.8381527
5-th percentile10.774848
Q112.784408
median18.005642
Q321.876883
95-th percentile25.631122
Maximum29.94628
Range20.108128
Interquartile range (IQR)9.0924747

Descriptive statistics

Standard deviation5.0399804
Coefficient of variation (CV)0.28344614
Kurtosis-1.1399125
Mean17.781087
Median Absolute Deviation (MAD)4.5566449
Skewness0.1427271
Sum25818.138
Variance25.401403
MonotonicityNot monotonic
2024-02-12T16:09:21.409432image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11.94401879 1
 
0.1%
19.72474865 1
 
0.1%
19.83252028 1
 
0.1%
19.37446947 1
 
0.1%
19.69152912 1
 
0.1%
19.29554031 1
 
0.1%
19.72808145 1
 
0.1%
19.92179591 1
 
0.1%
19.34096709 1
 
0.1%
20.19188016 1
 
0.1%
Other values (1442) 1442
99.3%
ValueCountFrequency (%)
9.838152682 1
0.1%
9.946903798 1
0.1%
10.05545612 1
0.1%
10.05987625 1
0.1%
10.10082919 1
0.1%
10.13347916 1
0.1%
10.1627243 1
0.1%
10.21183401 1
0.1%
10.21610818 1
0.1%
10.22799294 1
0.1%
ValueCountFrequency (%)
29.94628023 1
0.1%
29.84294655 1
0.1%
29.71800733 1
0.1%
29.64215075 1
0.1%
29.61154097 1
0.1%
29.49410883 1
0.1%
29.43490946 1
0.1%
29.36549566 1
0.1%
29.31076757 1
0.1%
29.16827805 1
0.1%

exp_price_median
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1452
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean355.96295
Minimum222.21471
Maximum477.74207
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.7 KiB
2024-02-12T16:09:21.573860image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum222.21471
5-th percentile265.09653
Q1288.10079
median357.75773
Q3418.65096
95-th percentile456.65128
Maximum477.74207
Range255.52736
Interquartile range (IQR)130.55017

Descriptive statistics

Standard deviation68.852344
Coefficient of variation (CV)0.19342559
Kurtosis-1.4823091
Mean355.96295
Median Absolute Deviation (MAD)67.196633
Skewness0.073972932
Sum516858.2
Variance4740.6453
MonotonicityNot monotonic
2024-02-12T16:09:21.755226image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
268.8281168 1
 
0.1%
468.2748266 1
 
0.1%
468.975588 1
 
0.1%
469.7014842 1
 
0.1%
468.1190817 1
 
0.1%
469.1372461 1
 
0.1%
467.4483653 1
 
0.1%
467.2305393 1
 
0.1%
463.793736 1
 
0.1%
463.6440478 1
 
0.1%
Other values (1442) 1442
99.3%
ValueCountFrequency (%)
222.2147082 1
0.1%
229.0138938 1
0.1%
234.3059508 1
0.1%
239.7475708 1
0.1%
240.7085542 1
0.1%
240.9689382 1
0.1%
241.2404546 1
0.1%
241.9556414 1
0.1%
244.1091381 1
0.1%
245.9773241 1
0.1%
ValueCountFrequency (%)
477.7420676 1
0.1%
477.5801024 1
0.1%
477.4952323 1
0.1%
477.1833845 1
0.1%
476.8435811 1
0.1%
476.8087927 1
0.1%
476.5145827 1
0.1%
476.1798873 1
0.1%
475.259737 1
0.1%
475.0668493 1
0.1%

exp_price_q1
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1452
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean344.19909
Minimum209.07976
Maximum461.80611
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.7 KiB
2024-02-12T16:09:21.916569image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum209.07976
5-th percentile255.92858
Q1280.21507
median345.67694
Q3404.30105
95-th percentile440.93019
Maximum461.80611
Range252.72635
Interquartile range (IQR)124.08598

Descriptive statistics

Standard deviation66.112478
Coefficient of variation (CV)0.19207627
Kurtosis-1.4499727
Mean344.19909
Median Absolute Deviation (MAD)63.407738
Skewness0.066104856
Sum499777.08
Variance4370.8597
MonotonicityNot monotonic
2024-02-12T16:09:22.221526image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
260.8767058 1
 
0.1%
455.1865728 1
 
0.1%
455.8118395 1
 
0.1%
456.8447697 1
 
0.1%
455.0577715 1
 
0.1%
456.3659371 1
 
0.1%
454.3654713 1
 
0.1%
454.0323842 1
 
0.1%
450.9347103 1
 
0.1%
450.2104006 1
 
0.1%
Other values (1442) 1442
99.3%
ValueCountFrequency (%)
209.0797589 1
0.1%
215.848487 1
0.1%
225.5016907 1
0.1%
227.1471952 1
0.1%
227.3521011 1
0.1%
227.7895619 1
0.1%
227.9596744 1
0.1%
231.5791551 1
0.1%
231.7592633 1
0.1%
232.0835685 1
0.1%
ValueCountFrequency (%)
461.8061134 1
0.1%
461.1176601 1
0.1%
459.9123366 1
0.1%
459.6565524 1
0.1%
459.5933436 1
0.1%
459.3952805 1
0.1%
459.1048871 1
0.1%
458.9618108 1
0.1%
458.2055684 1
0.1%
458.1779909 1
0.1%

exp_price_q3
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1452
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean368.14053
Minimum236.12832
Maximum496.22109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.7 KiB
2024-02-12T16:09:22.403639image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum236.12832
5-th percentile274.4209
Q1296.64002
median371.53807
Q3433.48253
95-th percentile472.80588
Maximum496.22109
Range260.09277
Interquartile range (IQR)136.84251

Descriptive statistics

Standard deviation71.750583
Coefficient of variation (CV)0.19489998
Kurtosis-1.5072901
Mean368.14053
Median Absolute Deviation (MAD)71.657129
Skewness0.080641269
Sum534540.04
Variance5148.1461
MonotonicityNot monotonic
2024-02-12T16:09:22.591903image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
277.0146905 1
 
0.1%
481.7831653 1
 
0.1%
482.4736442 1
 
0.1%
482.9552962 1
 
0.1%
481.5777709 1
 
0.1%
482.3141981 1
 
0.1%
480.9385094 1
 
0.1%
480.8135031 1
 
0.1%
476.971056 1
 
0.1%
477.4309526 1
 
0.1%
Other values (1442) 1442
99.3%
ValueCountFrequency (%)
236.1283177 1
0.1%
242.9033175 1
0.1%
243.5344222 1
0.1%
249.9796359 1
0.1%
253.0390065 1
0.1%
254.3133654 1
0.1%
255.2893112 1
0.1%
255.3803475 1
0.1%
255.9684865 1
0.1%
256.4240246 1
0.1%
ValueCountFrequency (%)
496.2210914 1
0.1%
495.853133 1
0.1%
495.2557271 1
0.1%
495.0299574 1
0.1%
494.5175112 1
0.1%
494.2010943 1
0.1%
493.8633035 1
0.1%
493.2866066 1
0.1%
492.9902614 1
0.1%
492.4547696 1
0.1%

exp_price_kurtosis
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1452
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.040792528
Minimum0.00041912186
Maximum0.15358268
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.7 KiB
2024-02-12T16:09:22.943272image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0.00041912186
5-th percentile0.017584901
Q10.028554683
median0.03815314
Q30.05009347
95-th percentile0.068430687
Maximum0.15358268
Range0.15316356
Interquartile range (IQR)0.021538787

Descriptive statistics

Standard deviation0.018536647
Coefficient of variation (CV)0.4544128
Kurtosis6.3969965
Mean0.040792528
Median Absolute Deviation (MAD)0.010768585
Skewness1.7301932
Sum59.23075
Variance0.00034360728
MonotonicityNot monotonic
2024-02-12T16:09:23.110271image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.02650364493 1
 
0.1%
0.01516347411 1
 
0.1%
0.03172161851 1
 
0.1%
0.02113064333 1
 
0.1%
0.03038780573 1
 
0.1%
0.02870640302 1
 
0.1%
0.02769465851 1
 
0.1%
0.03564455738 1
 
0.1%
0.03252765703 1
 
0.1%
0.02797636469 1
 
0.1%
Other values (1442) 1442
99.3%
ValueCountFrequency (%)
0.0004191218638 1
0.1%
0.00196139444 1
0.1%
0.002514180793 1
0.1%
0.002525490529 1
0.1%
0.003298163687 1
0.1%
0.004201912704 1
0.1%
0.007060763888 1
0.1%
0.00714397768 1
0.1%
0.007168621305 1
0.1%
0.007878158712 1
0.1%
ValueCountFrequency (%)
0.1535826849 1
0.1%
0.1424642012 1
0.1%
0.1404175656 1
0.1%
0.1397095531 1
0.1%
0.1376849245 1
0.1%
0.1353774356 1
0.1%
0.1352992516 1
0.1%
0.135049969 1
0.1%
0.1349703954 1
0.1%
0.1317093409 1
0.1%

exp_price_skew
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1452
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.14874172
Minimum0.094019188
Maximum0.28096379
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.7 KiB
2024-02-12T16:09:23.277717image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0.094019188
5-th percentile0.11134776
Q10.12832053
median0.14715003
Q30.16538953
95-th percentile0.19183998
Maximum0.28096379
Range0.1869446
Interquartile range (IQR)0.037068999

Descriptive statistics

Standard deviation0.027328774
Coefficient of variation (CV)0.18373308
Kurtosis3.198174
Mean0.14874172
Median Absolute Deviation (MAD)0.018516541
Skewness1.1609193
Sum215.97298
Variance0.00074686191
MonotonicityNot monotonic
2024-02-12T16:09:23.437756image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1268148083 1
 
0.1%
0.1206555825 1
 
0.1%
0.1265427599 1
 
0.1%
0.125971138 1
 
0.1%
0.1295546415 1
 
0.1%
0.1260746427 1
 
0.1%
0.128585436 1
 
0.1%
0.1366910158 1
 
0.1%
0.1286141862 1
 
0.1%
0.1325886502 1
 
0.1%
Other values (1442) 1442
99.3%
ValueCountFrequency (%)
0.09401918756 1
0.1%
0.09740256584 1
0.1%
0.09838090648 1
0.1%
0.09949283491 1
0.1%
0.1020213008 1
0.1%
0.102089883 1
0.1%
0.1022636706 1
0.1%
0.1034742472 1
0.1%
0.1035831753 1
0.1%
0.1039173628 1
0.1%
ValueCountFrequency (%)
0.2809637916 1
0.1%
0.2745775414 1
0.1%
0.2741823107 1
0.1%
0.2728853256 1
0.1%
0.2726848568 1
0.1%
0.270982515 1
0.1%
0.2696645554 1
0.1%
0.2693594666 1
0.1%
0.2689860845 1
0.1%
0.2671256278 1
0.1%

days
Categorical

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size22.7 KiB
21
786 
20
468 
22
87 
23
 
62
18
 
49

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2904
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row22
2nd row21
3rd row20
4th row21
5th row23

Common Values

ValueCountFrequency (%)
21 786
54.1%
20 468
32.2%
22 87
 
6.0%
23 62
 
4.3%
18 49
 
3.4%

Length

2024-02-12T16:09:23.582984image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-02-12T16:09:23.708516image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
21 786
54.1%
20 468
32.2%
22 87
 
6.0%
23 62
 
4.3%
18 49
 
3.4%

Most occurring characters

ValueCountFrequency (%)
2 1490
51.3%
1 835
28.8%
0 468
 
16.1%
3 62
 
2.1%
8 49
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2904
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1490
51.3%
1 835
28.8%
0 468
 
16.1%
3 62
 
2.1%
8 49
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Common 2904
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1490
51.3%
1 835
28.8%
0 468
 
16.1%
3 62
 
2.1%
8 49
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2904
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1490
51.3%
1 835
28.8%
0 468
 
16.1%
3 62
 
2.1%
8 49
 
1.7%

r
Real number (ℝ)

Distinct329
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7344697
Minimum0
Maximum5.95
Zeros10
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size22.7 KiB
2024-02-12T16:09:23.872547image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.02
Q10.09
median1.62
Q32.4025
95-th percentile5.52
Maximum5.95
Range5.95
Interquartile range (IQR)2.3125

Descriptive statistics

Standard deviation1.7073413
Coefficient of variation (CV)0.98435927
Kurtosis-0.1203836
Mean1.7344697
Median Absolute Deviation (MAD)1.49
Skewness0.88900046
Sum2518.45
Variance2.9150144
MonotonicityNot monotonic
2024-02-12T16:09:24.095276image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.05 66
 
4.5%
0.09 61
 
4.2%
0.04 57
 
3.9%
0.08 49
 
3.4%
0.03 43
 
3.0%
0.01 40
 
2.8%
0.1 34
 
2.3%
0.06 32
 
2.2%
0.02 26
 
1.8%
0.07 25
 
1.7%
Other values (319) 1019
70.2%
ValueCountFrequency (%)
0 10
 
0.7%
0.01 40
2.8%
0.02 26
 
1.8%
0.03 43
3.0%
0.04 57
3.9%
0.05 66
4.5%
0.06 32
2.2%
0.07 25
 
1.7%
0.08 49
3.4%
0.09 61
4.2%
ValueCountFrequency (%)
5.95 1
 
0.1%
5.81 1
 
0.1%
5.79 1
 
0.1%
5.76 1
 
0.1%
5.73 1
 
0.1%
5.67 1
 
0.1%
5.62 1
 
0.1%
5.61 1
 
0.1%
5.6 2
0.1%
5.59 3
0.2%

prob_itm
Real number (ℝ)

Distinct1378
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.50024526
Minimum0.423696
Maximum0.81303
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.7 KiB
2024-02-12T16:09:24.296888image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0.423696
5-th percentile0.4874404
Q10.4947435
median0.500286
Q30.505502
95-th percentile0.5124021
Maximum0.81303
Range0.389334
Interquartile range (IQR)0.0107585

Descriptive statistics

Standard deviation0.012429098
Coefficient of variation (CV)0.024846009
Kurtosis280.14272
Mean0.50024526
Median Absolute Deviation (MAD)0.005417
Skewness10.575984
Sum726.35612
Variance0.00015448249
MonotonicityNot monotonic
2024-02-12T16:09:24.464960image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.501342 3
 
0.2%
0.499996 3
 
0.2%
0.49891 3
 
0.2%
0.502596 2
 
0.1%
0.507628 2
 
0.1%
0.501574 2
 
0.1%
0.50863 2
 
0.1%
0.500506 2
 
0.1%
0.501044 2
 
0.1%
0.4986 2
 
0.1%
Other values (1368) 1429
98.4%
ValueCountFrequency (%)
0.423696 1
0.1%
0.425858 1
0.1%
0.436504 1
0.1%
0.438508 1
0.1%
0.442782 1
0.1%
0.444334 1
0.1%
0.451478 1
0.1%
0.462156 1
0.1%
0.462254 1
0.1%
0.464796 1
0.1%
ValueCountFrequency (%)
0.81303 1
0.1%
0.568636 1
0.1%
0.565672 1
0.1%
0.547784 1
0.1%
0.541946 1
0.1%
0.5337 1
0.1%
0.531114 1
0.1%
0.529058 1
0.1%
0.528618 1
0.1%
0.522326 1
0.1%

Interactions

2024-02-12T16:09:16.477596image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:52.607270image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:54.332568image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:55.834713image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:57.441924image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:58.943561image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:00.518728image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:02.522798image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:04.228873image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:05.946617image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:07.535320image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:09.267886image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:12.201167image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:14.440306image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:16.604084image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:52.721874image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:54.429902image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:55.933396image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:57.543315image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:59.046033image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:00.814530image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:02.656149image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:04.384655image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:06.051859image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:07.640676image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:09.379078image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:12.363024image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:14.583199image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:16.707144image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:52.823100image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:54.528161image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:56.030492image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:57.641265image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:59.148856image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:00.919272image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:02.771095image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:04.545951image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:06.161287image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:07.740887image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:09.494186image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:12.666456image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:14.729699image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:16.815015image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:52.933913image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:54.627678image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:56.132306image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:57.743320image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:59.252551image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:01.028670image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:02.888604image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:04.660272image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:06.275354image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:07.841338image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:09.603928image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:12.828018image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:14.836585image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:16.923342image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:53.177967image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:54.726113image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:56.234049image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:57.840804image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:59.360366image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:01.135613image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:02.999629image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:04.763998image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:06.387304image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:07.943193image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:09.716750image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:12.983460image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:14.932748image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:17.034287image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:53.286985image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:54.831381image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:56.338660image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:57.946408image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:59.467610image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:01.248444image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:03.120359image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:04.869983image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:06.507467image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:08.049479image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:09.833220image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:13.135220image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:15.041841image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:17.143434image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:53.404343image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:54.945878image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:56.444848image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:58.054843image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:59.578643image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:01.416790image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:03.238414image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:04.988192image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:06.634342image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:08.365106image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:10.007948image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:13.251120image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:15.210603image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:17.269826image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:53.538247image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:55.067776image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:56.562677image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:58.172392image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:59.700198image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:01.574437image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:03.368382image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:05.114601image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:06.758298image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:08.486488image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:10.279518image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:13.376969image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:15.380415image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:17.422658image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:53.645453image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:55.169801image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:56.664523image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:58.274447image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:59.810137image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:01.705738image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:03.480250image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:05.220826image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:06.861694image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:08.592064image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:10.640647image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:13.525591image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:15.516567image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:17.556917image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:53.752337image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:55.272599image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:56.768972image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:58.378184image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:59.919895image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:01.847221image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:03.597285image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:05.336297image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:06.965510image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:08.697264image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:10.916293image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:13.688831image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:15.623589image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:17.855498image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:53.859489image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:55.377070image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:56.874775image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:58.488831image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:00.031397image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:01.965398image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:03.714190image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:05.449373image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:07.073341image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:08.802900image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:11.193770image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:13.899339image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:15.746383image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:17.975695image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:53.983974image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:55.496581image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:57.009872image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:58.607796image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:00.163796image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:02.143209image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:03.848125image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:05.577601image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:07.194449image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:08.925429image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:11.598976image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:14.082327image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:15.925380image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:18.096749image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:54.108989image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:55.611757image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:57.218128image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:58.723857image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:00.287808image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:02.265241image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:03.977752image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:05.697332image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:07.311480image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:09.042563image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:11.853083image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:14.205048image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:16.203791image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:18.205430image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:54.217657image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:55.718352image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:57.327144image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:08:58.828652image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:00.397946image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:02.390889image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:04.102388image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:05.825613image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:07.418737image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:09.150044image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:12.047212image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:14.317893image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-12T16:09:16.319165image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Correlations

2024-02-12T16:09:24.584249image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
daysexp_call_priceexp_priceexp_price_kurtosisexp_price_maxexp_price_medianexp_price_minexp_price_q1exp_price_q3exp_price_skewexp_price_stdlast_quoteprob_itmrstrike
days1.0000.1810.0890.1780.1270.0890.0600.0840.0940.1890.1820.0890.0050.1550.089
exp_call_price0.1811.0000.7690.6560.8860.7680.6820.7530.7850.7860.9920.7680.064-0.1010.767
exp_price0.0890.7691.0000.2060.9641.0000.9810.9990.9990.2810.7811.000-0.039-0.1601.000
exp_price_kurtosis0.1780.6560.2061.0000.3890.2040.0910.1840.2270.8630.6560.2040.0160.0070.204
exp_price_max0.1270.8860.9640.3891.0000.9640.9150.9570.9710.4800.8960.964-0.037-0.1710.964
exp_price_median0.0890.7681.0000.2040.9641.0000.9820.9990.9990.2790.7791.000-0.039-0.1601.000
exp_price_min0.0600.6820.9810.0910.9150.9821.0000.9870.9760.1520.6930.982-0.040-0.1520.982
exp_price_q10.0840.7530.9990.1840.9570.9990.9871.0000.9980.2560.7640.999-0.039-0.1580.999
exp_price_q30.0940.7850.9990.2270.9710.9990.9760.9981.0000.3050.7960.999-0.039-0.1630.999
exp_price_skew0.1890.7860.2810.8630.4800.2790.1520.2560.3051.0000.7870.279-0.001-0.0150.279
exp_price_std0.1820.9920.7810.6560.8960.7790.6930.7640.7960.7871.0000.779-0.026-0.0990.779
last_quote0.0890.7681.0000.2040.9641.0000.9820.9990.9990.2790.7791.000-0.039-0.1601.000
prob_itm0.0050.064-0.0390.016-0.037-0.039-0.040-0.039-0.039-0.001-0.026-0.0391.0000.013-0.045
r0.155-0.101-0.1600.007-0.171-0.160-0.152-0.158-0.163-0.015-0.099-0.1600.0131.000-0.160
strike0.0890.7671.0000.2040.9641.0000.9820.9990.9990.2790.7791.000-0.045-0.1601.000

Missing values

2024-02-12T16:09:18.387818image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-02-12T16:09:18.639462image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

last_quotestrikeexp_priceexp_call_priceexp_price_minexp_price_maxexp_price_stdexp_price_medianexp_price_q1exp_price_q3exp_price_kurtosisexp_price_skewdaysrprob_itm
Date
2018-01-02268.81269.0269.0778644.798478214.131384327.50796511.944019268.828117260.876706277.0146910.0265040.126815221.280.494226
2018-01-03270.47270.0270.6884324.876650222.222567332.90134411.373519270.457731262.911236278.2242740.0349410.122681211.290.515890
2018-01-04271.56272.0271.7866154.328733223.655644330.20996711.120377271.568078264.168892279.1539840.0297650.121482201.290.484650
2018-01-05273.41273.0273.6484544.905581221.289764331.78020711.489731273.407691265.762322281.2654820.0192910.126896211.280.513998
2018-01-08273.94274.0274.1935454.856711225.354348340.16850811.953757273.937208265.993480282.0953480.0331560.130088231.270.497914
2018-01-09274.53275.0274.7707864.526757226.991580341.28520811.642630274.507259266.792465282.4775980.0369200.137266221.300.482946
2018-01-10274.08274.0274.3262364.678939226.152762327.98207711.337448274.082970266.555532281.8411710.0245790.125194211.270.502882
2018-01-11276.09276.0276.3132824.559128227.016141333.62101311.054388276.090230268.750520283.6394550.0336110.119514201.310.503206
2018-01-12277.91278.0278.1373944.626119229.520759333.18208711.439341277.915324270.302269285.7354400.0169520.117595211.320.496888
2018-01-16276.96275.0277.2152525.863150230.342260338.66413011.778039276.951833269.137261285.0129030.0175850.131356221.310.565672
last_quotestrikeexp_priceexp_call_priceexp_price_minexp_price_maxexp_price_stdexp_price_medianexp_price_q1exp_price_q3exp_price_kurtosisexp_price_skewdaysrprob_itm
Date
2023-12-13470.53471.0471.2218349.930496367.442520610.74901424.762298470.560873454.253986487.4525320.0652730.158496235.530.492936
2023-12-14472.02472.0472.62155010.085744366.804722605.48948524.624183471.986333455.716187488.8399130.0533790.154712225.520.499798
2023-12-15469.41469.0470.04450110.124837359.315578588.02141624.177843469.430448453.457036485.9478730.0437040.155387215.540.507232
2023-12-18472.00472.0472.5492709.309687382.924099597.96717322.745275471.983556456.973276487.5546210.0467160.145628185.540.499682
2023-12-20468.07468.0468.73733610.466913359.824682592.88861625.440380467.999382451.272692485.4739380.0426530.163999235.510.499996
2023-12-21472.70473.0473.37096710.164281374.268783610.36081125.136092472.732753456.084931489.9101510.0380070.158242225.500.495762
2023-12-22473.68474.0474.31722510.025319382.036480602.06099724.825530473.660395457.230750490.7385300.0356110.158126215.540.494620
2023-12-27476.47476.0477.21854210.894740360.410992607.21466725.917616476.514583459.395281494.2010940.0634160.166208235.530.507994
2023-12-28476.73477.0477.43947810.520456374.087729602.83849125.944512476.808793459.593344494.5175110.0506340.160785225.550.497016
2023-12-29475.31475.0475.97040810.752795367.242512617.41707125.854965475.259737458.177991492.9902610.0550380.160526215.570.503988